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This work concerns a fluorescence optical projection tomography system for low scattering tissue, like lymph nodes, with angular-domain rejection of highly scattered photons. In this regime, filtered backprojection (FBP) image reconstruction has been shown to provide reasonable quality images, yet here a comparison of image quality between images obtained by FBP and iterative image reconstruction with a Monte Carlo generated system matrix, demonstrate measurable improvements with the iterative method. Through simulated and experimental phantoms, iterative algorithms consistently outperformed FBP in terms of contrast and spatial resolution. Moreover, when projection number was reduced, in order to reduce total imaging time, iterative reconstruction suppressed artifacts that hampered the performance of FBP reconstruction (structural similarity of the reconstructed images with “truth” was improved from 0.15 ± 1.2 × 10−3to 0.66 ± 0.02); and although the system matrix was generated for homogenous optical properties, when heterogeneity (62.98 cm-1variance inµs) was introduced to simulated phantoms, the results were still comparable (structural similarity homo: 0.67 ± 0.02 vs hetero: 0.66 ± 0.02).
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Enhancement-constrained acceleration: A robust reconstruction framework in breast DCE-MRI
In patients with dense breasts or at high risk of breast cancer, dynamic contrast enhanced MRI (DCE-MRI) is a highly sensitive diagnostic tool. However, its specificity is highly variable and sometimes low; quantitative measurements of contrast uptake parameters may improve specificity and mitigate this issue. To improve diagnostic accuracy, data need to be captured at high spatial and temporal resolution. While many methods exist to accelerate MRI temporal resolution, not all are optimized to capture breast DCE-MRI dynamics. We propose a novel, flexible, and powerful framework for the reconstruction of highly-undersampled DCE-MRI data: enhancement-constrained acceleration (ECA). Enhancement-constrained acceleration uses an assumption of smooth enhancement at small time-scale to estimate points of smooth enhancement curves in small time intervals at each voxel. This method is tested in silico with physiologically realistic virtual phantoms, simulating state-of-the-art ultrafast acquisitions at 3.5s temporal resolution reconstructed at 0.25s temporal resolution (demo code available here). Virtual phantoms were developed from real patient data and parametrized in continuous time with arterial input function (AIF) models and lesion enhancement functions. Enhancement-constrained acceleration was compared to standard ultrafast reconstruction in estimating the bolus arrival time and initial slope of enhancement from reconstructed images. We found that the ECA method reconstructed images at 0.25s temporal resolution with no significant loss in image fidelity, a 4x reduction in the error of bolus arrival time estimation in lesions ( p < 0.01) and 11x error reduction in blood vessels ( p < 0.01). Our results suggest that ECA is a powerful and versatile tool for breast DCE-MRI.
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- Award ID(s):
- 1654076
- PAR ID:
- 10331202
- Editor(s):
- Chen, Xi
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 16
- Issue:
- 10
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0258621
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0258621
